Skip to main content
NCBI home page
American Journal of Public Health logoLink to American Journal of Public Health
. 1998 Sep;88(9):1377–1380. doi: 10.2105/ajph.88.9.1377

Evaluating cluster alarms: a space-time scan statistic and brain cancer in Los Alamos, New Mexico.

M Kulldorff 1, W F Athas 1, E J Feurer 1, B A Miller 1, C R Key 1
PMCID: PMC1509064  PMID: 9736881

Abstract

OBJECTIVES: This article presents a space-time scan statistic, useful for evaluating space-time cluster alarms, and illustrates the method on a recent brain cancer cluster alarms in Los Alamos, NM. METHODS: The space-time scan statistic accounts for the preselection bias and multiple testing inherent in a cluster alarm. Confounders and time trends can be adjusted for. RESULTS: The observed excess of brain cancer in Los Alamos was not statistically significant. CONCLUSIONS: The space-time scan statistic is useful as a screening tool for evaluating which cluster alarms merit further investigation and which clusters are probably chance occurrences.

Full text

PDF
1377

Selected References

These references are in PubMed. This may not be the complete list of references from this article.

  1. Chen R., Connelly R. R., Mantel N. Analysing post-alarm data in a monitoring system in order to accept or reject the alarm. Stat Med. 1993 Oct;12(19-20):1807–1812. doi: 10.1002/sim.4780121908. [DOI] [PubMed] [Google Scholar]
  2. Jacquez G. M. A k nearest neighbour test for space-time interaction. Stat Med. 1996 Sep 15;15(17-18):1935–1949. doi: 10.1002/(sici)1097-0258(19960930)15:18<1935::aid-sim406>3.0.co;2-i. [DOI] [PubMed] [Google Scholar]
  3. Kulldorff M., Nagarwalla N. Spatial disease clusters: detection and inference. Stat Med. 1995 Apr 30;14(8):799–810. doi: 10.1002/sim.4780140809. [DOI] [PubMed] [Google Scholar]
  4. Mantel N. The detection of disease clustering and a generalized regression approach. Cancer Res. 1967 Feb;27(2):209–220. [PubMed] [Google Scholar]
  5. Ranta J., Pitkäniemi J., Karvonen M., Virtala E., Rusanen J., Colpaert A., Naukkarinen A., Tuomilehto J. Detection of overall space-time clustering in a non-uniformly distributed population. DiMe Study Group. Stat Med. 1996 Dec 15;15(23):2561–2572. doi: 10.1002/(SICI)1097-0258(19961215)15:23<2561::AID-SIM370>3.0.CO;2-M. [DOI] [PubMed] [Google Scholar]
  6. Raubertas R. F. Spatial and temporal analysis of disease occurrence for detection of clustering. Biometrics. 1988 Dec;44(4):1121–1129. [PubMed] [Google Scholar]
  7. Turnbull B. W., Iwano E. J., Burnett W. S., Howe H. L., Clark L. C. Monitoring for clusters of disease: application to leukemia incidence in upstate New York. Am J Epidemiol. 1990 Jul;132(1 Suppl):S136–S143. doi: 10.1093/oxfordjournals.aje.a115775. [DOI] [PubMed] [Google Scholar]
  8. Wallenstein S. A test for detection of clustering over time. Am J Epidemiol. 1980 Mar;111(3):367–372. doi: 10.1093/oxfordjournals.aje.a112908. [DOI] [PubMed] [Google Scholar]
  9. Wallenstein S. A test for detection of clustering over time. Am J Epidemiol. 1980 Mar;111(3):367–372. doi: 10.1093/oxfordjournals.aje.a112908. [DOI] [PubMed] [Google Scholar]
  10. Wallenstein S., Weinberg C. R., Gould M. Testing for a pulse in seasonal event data. Biometrics. 1989 Sep;45(3):817–830. [PubMed] [Google Scholar]
  11. Weinstock M. A. A generalised scan statistic test for the detection of clusters. Int J Epidemiol. 1981 Sep;10(3):289–293. doi: 10.1093/ije/10.3.289. [DOI] [PubMed] [Google Scholar]

Articles from American Journal of Public Health are provided here courtesy of American Public Health Association

RESOURCES